Identification of the regulatory proteins in human pancreatic cancers treated with Trichostatin A by 2D-PAGE maps and multivariate statistical analysis

Anal Bioanal Chem. 2004 Aug;379(7-8):992-1003. doi: 10.1007/s00216-004-2707-x. Epub 2004 Jul 15.


In this paper, principal component analysis (PCA) is applied to a spot quantity dataset comprising 435 spots detected in 18 samples belonging to two different cell lines (Paca44 and T3M4) of control (untreated) and drug-treated pancreatic ductal carcinoma cells. The aim of the study was the identification of the differences occurring between the proteomic patterns of the two investigated cell lines and the evaluation of the effect of the drug Trichostatin A on the protein content of the cells. PCA turned out to be a successful tool for the identification of the classes of samples present in the dataset. Moreover, the loadings analysis allowed the identification of the differentially expressed spots, which characterise each group of samples. The treatment of both the cell lines with Trichostatin A therefore showed an appreciable effect on the proteomic pattern of the treated samples. Identification of some of the most relevant spots was also performed by mass spectrometry.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Analysis of Variance
  • Antineoplastic Agents / therapeutic use*
  • Cell Line, Tumor
  • Electrophoresis, Gel, Two-Dimensional / methods
  • Humans
  • Hydroxamic Acids / therapeutic use*
  • Multivariate Analysis
  • Neoplasm Proteins / analysis*
  • Pancreatic Neoplasms / chemistry*
  • Pancreatic Neoplasms / drug therapy*
  • Pancreatic Neoplasms / metabolism
  • Principal Component Analysis / methods
  • Proteomics
  • Software
  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / methods


  • Antineoplastic Agents
  • Hydroxamic Acids
  • Neoplasm Proteins
  • trichostatin A